The subject matter disclosed herein relates to computed tomography (CT) imaging systems and, in particular, to a multi-material decomposition method and visualization method using dual energy x-ray sources for CT imaging systems.
Typically, in CT imaging systems, an x-ray source emits a fan-shaped or a cone-shaped x-ray beam toward a subject or object, such as a patient or a luggage item positioned on a support. The x-ray beam impinges on a detector assembly at the far side of the subject, comprising a plurality of detector modules, where the intensity of the x-ray beam detected is a function of the attenuation of the x-ray beam by the subject. In known “third generation” CT systems, the x-ray source and the detector assembly partially enclose the subject in a rotatable gantry structure. Data representing the intensity of the detected x-ray beam is collected across a range of gantry angles, and the data are ultimately processed to form an image.
A CT imaging system may be configured as an energy discriminating, a multi energy, and/or a dual energy CT imaging system. Dual energy CT imaging is an imaging procedure in which multiple scans are made of the same target under the same conditions at two different energy levels, or energy spectra, and is used to identify different materials in the target. For example, soft tissue and similar materials having a relatively low density typically attenuate incident x-rays to a lesser degree than does a relatively high density material, such as bone or an iodine contrast agent. It is appreciated in the relevant art that CT imaging performed at two imaging scans, one at a higher x-ray tube voltage level, such as 110 to 150 kVp, and another imaging scan performed at a lower x-ray tube voltage level, such as 60 to 80 kVp, provides more information about the materials being scanned than does a single-energy CT imaging scan.
Data obtained from a dual energy CT image scan can be used to reconstruct images using basis material decomposition computation processes. The generated images are representative of a pair of selected basis material densities. In addition to material density images, dual energy projection data can be used to produce a new image with x-ray attenuation coefficients equivalent to a selected monochromatic energy. Such a monochromatic image may include an image where the intensity values of image voxels are assigned as if a CT image were created by collecting projection data from the subject with a monochromatic x-ray beam.
In the medical imaging field, for example, dual energy CT scans may be performed at a relatively low energy' level of about 80 kVp, and at a relatively ‘high energy’ level of about 140 kVp, where the scans may be acquired “back-to-back” or interleaved. Special filters may be placed between the x-ray source and energy sensitive detectors such that different detector rows collect projections of different x-ray energy spectra.
The measurements may be obtained by: (i) scanning with two distinctive energy spectra; (ii) detecting photon energy according to energy deposition in the detector, and (iii) photon counting with multiple energy bins. In the absence of object scatter, the CT system can derive the information about object attenuation versus energy based on the signal from two or more regions of photon energy in the spectrum, for example, the low-energy and the high-energy portions of the incident x-ray spectrum. In medical CT, two physical processes dominate the x-ray attenuation: Compton scatter and the photoelectric effect. The detected signals from two energy regions usually provide sufficient information to resolve the energy dependence of the material being imaged. Furthermore, detected signals from the two energy regions provide sufficient information to determine the relative composition of an object composed of two materials.
Using the images obtained during these CT scans, one can generate basis material density images and monochromatic images, that is, images that represent the effect of performing a computed tomography scan with an ideal monochromatic tube source. Given a pair of material density images, it is possible to generate other basis material image pairs. For example, from a water and iodine image of the same anatomy, it is possible to generate a different pair of material density images such as calcium and gadolinium. Similarly, by using a pair of basis material images, one can generate a pair of monochromatic images, each at a specific x-ray energy. Similarly, one can obtain, from a pair of monochromatic images, a pair of basis material image pairs, or a pair of monochromatic images at different energies.
Conventional material basis decompositions utilize the concept that, in the energy region for medical CT, the x-ray attenuation of any given material can be represented by a proper density mix of two other materials, commonly denoted as “basis materials.” The basis material decomposition computing process produces two CT images, each representing the equivalent density of one of the basis materials. Since a material density is independent of x-ray photon energy, the two CT images are largely free of beam-hardening artifacts. An operator can choose the basis material to target a certain material of interest, for example, to enhance the image contrast.
Thus, dual-energy CT is an imaging modality that extends the capabilities of standard CT, and enables the estimation of the full linear attenuation curve for each voxel in the image volume, instead of a scalar image in Hounsfield units. As explained above, this is achieved by acquiring X-ray projections at two different energy spectra and, under careful calibration, reconstructing a material-decomposed image pair. Each co-registered voxel of this pair is a two-dimensional vector corresponding to an estimate, consistent with projection data, for the density of two pre-selected materials making up that voxel. Because the space of linear attenuation curves can be described as a two-dimensional manifold plus a residual difference which is too small to be measured under current CT technology, this decomposition procedure is essentially limited to the specification of only two materials.
Typically, dual-energy CT provides estimates for a linear attenuation curve of an imaged object at each pixel location. However, a more desirable measurement would be a mass attenuation curve, which is the linear attenuation curve multiplied by a respective material density. Thus, the mass attenuation curve is density independent, and it shares with the linear attenuation curve the property that it can be represented as a weighted sum of the curves of other materials. However, the mass attenuation curve has an additional property that the weights in the sum have a defined physical meaning: that they are the mass fractions of the constituent materials in the mix. Therefore, their weights should add to “unity,” or one.
As such, assuming that the mass fractions add to one, and that the mass attenuation coefficients relate back to the linear attenuation coefficients via their respective densities, an additional constraint is thereby imposed on a resulting system of equations that enables determination of at least a third material in a three material decomposition. Thus, triple material decomposition is possible if certain assumptions can be made regarding this additional constraint.
Solutions include an assumed relationship between given materials and the mixture by using a physicochemical model, as an example. One such solution includes assuming the mixture is an ideal solution, which implies that a volume of the solution at a given temperature and pressure is equal to the volume of its constituent parts at the same temperature and pressure. Under this assumption, the linear attenuation coefficients are thus assumed to be the volume fractions of the constituent materials in the mixture. As such, they add to one, providing an additional constraint over a two-material system and allowing a third material to be included in a decomposition that derives from two scans at different energies, resulting in three materials or a material triplet.
Thus, although an object to be imaged typically includes several materials, the object may be visualized having three top, or primary, materials selected for visualization. Once the three materials are determined as a material triplet, it is typically desirable to generate images of the three materials in order to diagnose a medical condition or to view images of materials of a security baggage scanner, as examples.
However, although a three material decomposition represents a dramatic improvement over a two material decomposition, which itself is a dramatic improvement over conventional single energy imaging, a three material combination is nevertheless a simplification that can cause confusion when viewing results. For instance, although an ability to view contrast agent as one of the materials of the material triplet may improve an ability to diagnose a pathology or condition, contrast agent displaces other materials within an image. Thus, it is possible that an image of a contrast agent as one of the materials of the material triplet may yield misleading results and blood flow, as an example, may be excluded and displaced by the contrast agent.
Additionally, a three material solution reveals three images as distinct and specific materials. However, as stated, a three material solution is itself a simplification, and some materials may not fall cleanly into one or another of the material triplet, despite the best material combination being selected to represent the overall set of materials being imaged.
Thus, there is a need for additional processing or manipulation of images in a three material system to better visualize an object being imaged.